1 Knowledge and Information Flows in a Hybrid Learning Space: the students’ perceptions Draft version of: Trentin, G. (2015). Knowledge and Information Flows in a Hybrid Learning Space: the students’ perceptions. Journal of Interactive Learning Research, 26(4), 403-429. NOT FOR DISTRIBUTION Guglielmo Trentin Institute for Educational Technology, National Research Council, Genoa, Italy Abstract How much information and/or knowledge flows among the members of a collaborative learning group and between them and the external information/knowledge sources? Which stages of the collaborative process have the highest knowledge and information flows, respectively? These are the questions which the experiment described in this paper seeks to answer. The experiment involved 66 students from the University of Turin. After attending a couple of lessons on online communities of professionals and doing some basic reading, they were asked to develop, in small sub-groups, an artefact (using a wiki) to summarise what had been learnt. The students were also asked to make a quantitative and qualitative estimate of the information and knowledge flows which took place in the three different phases of studying, structuring and collaboratively developing the artefact. The stages with the highest knowledge flow index were found to be the study and structuring stages, while information flows were mainly in the actual writing of the artefact. INTRODUCTION Research into collaborative learning has often concentrated on the following key aspects: (a) choice of collaborative strategy (Diaper, & Sanger, 1993; Lazakidou, 2010; Zhang, Ayres, & Chan, 2013); (b) assessment of the learning results produced by that strategy (Macdonald, 2003; Brodie, & Irving, 2007; Strijbos, 2011); (c) assessment of
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Knowledge and Information Flows in a Hybrid Learning Space:
the students’ perceptions
Draft version of:
Trentin, G. (2015). Knowledge and Information Flows in a Hybrid Learning Space: the students’
perceptions. Journal of Interactive Learning Research, 26(4), 403-429.
NOT FOR DISTRIBUTION
Guglielmo Trentin
Institute for Educational Technology, National Research Council, Genoa, Italy
Abstract
How much information and/or knowledge flows among the members of a collaborative learning group
and between them and the external information/knowledge sources? Which stages of the collaborative
process have the highest knowledge and information flows, respectively? These are the questions which
the experiment described in this paper seeks to answer.
The experiment involved 66 students from the University of Turin. After attending a couple of lessons
on online communities of professionals and doing some basic reading, they were asked to develop, in
small sub-groups, an artefact (using a wiki) to summarise what had been learnt.
The students were also asked to make a quantitative and qualitative estimate of the information and
knowledge flows which took place in the three different phases of studying, structuring and
collaboratively developing the artefact.
The stages with the highest knowledge flow index were found to be the study and structuring stages, while
information flows were mainly in the actual writing of the artefact.
INTRODUCTION
Research into collaborative learning has often concentrated on the following key
how far the strategy has stimulated students’ active participation, as measured by their
contribution to the development of the pre-set product of the collaborative process
(Trentin, 2009; Judd, Kennedy, & Cropper, 2010).
Relatively little research has instead so far been done on the flows of information and
knowledge within a collaborating group, and to what extent these flows are conditioned
by (a) the collaborative strategy adopted, (b) the management of this strategy, (c) the
technological and non-technological tools used to develop it, and (d) the space within
which the process develops.
These aspects become more important when the space within which the collaborative
process develops is a hybridisation of physical (institutional and non-institutional)
spaces and spaces which are instantiable through mobile and web technologies. De
Souza and Silva (2007, p. 262) give the following definition of hybrid space, which can
be usefully applied to our experiment:
“Because mobile devices create a more dynamic relationship with the Internet,
embedding it in outdoor, everyday activities, we can no longer address the
disconnection between physical and digital spaces. I name this new type of space
‘hybrid space’. Hybrid spaces are mobile spaces, created by the constant movement of
users who carry portable devices continuously connected to the Internet and to other
users.”
The importance of studying information/knowledge flows
When proposing learning group activities in a hybrid learning space (HLS) to
students, it might be useful to find answers to the following questions: (a) what amount
of information and/or knowledge flows in the interaction, both among the members of a
collaborative learning group and from them and the external information/knowledge
sources; (b) which stages of the collaborative process have the highest indexes of
knowledge flow (KF) and information flow (IF), respectively (Nissen, 2002; Trentin,
2011a; Oliver, 2013)? And, once the phases/activities of a collaborative process
producing the highest KF have been identified, how can it be potentiated to optimise the
collaborative approach and enhance the peer learning process?
Starting from these underlying considerations, the experiment described below sought to
answer the following research questions:
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what types of flow develop within learning groups at different stages of a
collaborative strategy?
to what extent do KFs and IFs develop respectively?
Experimental premise
Although much has been written and hypothesised about the conceptual difference
between information and knowledge, two problems still need to be solved (Yeager,
2005; Jones, 2010):
the lack of clear criteria for understanding when there is a flow of information and
when there is instead an actual flow of knowledge at any given moment of the
cognitive process;
the high level of subjectivity in discriminating between information and knowledge.
In other words, even when agreement is reached as to the above-mentioned criteria,
their application continues to be subjective, i.e. no-one is able to decide better than
the person directly involved when acquired information remains just that and when
instead it is transformed into actual new knowledge.
For the latter reason, in the experiment described below we decided to ask the students
themselves to give their quantitative and qualitative estimates of the type of flows that
passed through their groups.
In order for this choice to lead to reliable results, one essential condition had to be
guaranteed, i.e. that students were instructed beforehand as to the difference between KF
and IF. The ideal context for this was offered by the course Network Technology and
Knowledge Flow 2012 (NT&KF-2012), in the last year of the second-level degree in
“Public and Political Communication” at the University of Turin. The main aim of the
course was in fact to understand how network and mobile technologies could foster and
potentiate KF at an organisational level.
After attending a couple of lessons on online communities of professionals (COPs)
and studying some basic reading about the specific topic, they were tested (with a
multiple-choice test) on their understanding of the key aspects of IF/KF, and on their
ability to distinguish one from the other. In the following stages of the experiment, only
the qualitative/quantitative estimates of IF/KF furnished by students who had scored at
least 70 out of 100 in the test were taken into account. In this way, lack of knowledge on
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this topic could not jeopardise the reliability of the data produced by the students and
used for the experiment.
THE THEORETICAL BASES OF THE EXPERIMENT
Before directly addressing the theme of KF/IF, students’ ideas on the respective
meanings of information and knowledge had in some way to be standardised.
For this purpose, the DIKW (Data, Information, Knowledge, Wisdom) model was used
(Rowley, 2007):
Wisdom is the recognition that knowledge patterns arise out of fundamental
principles and the understanding of what those principles are;
Knowledge is represented by patterns among data, information and possibly other
knowledge. These patterns do not actually constitute knowledge until they are
understood;
Information is represented by relationships between data and possibly other
information;
Data is an item or event out of the context with no relation to other things.
For the specific aims of the experiment, most attention was obviously given to the
information and knowledge planes, their mutual influence, and above all the process by
which information is transformed into new knowledge.
In a hybrid learning space (HLS), a large portion of interactive flows is supported and
sometimes governed by mobile and network technologies (NMTs). Students were thus
advised to analyse the KFs/IFs from the points of view of both computer-mediated
communication (CMC) and communication theories.
Communication theory and information flow
Figure 1 shows the diagram of a communication system as conceived by Shannon and
Weaver (1949): an information source, an information codification and transmission
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unit, a transmission channel with noise interference1, an information receiver and
decodification unit, the destination of the information.
Figure 1 – Communication flow according to the model of Shannon and Weaver (1949).
This type of communication is at the basis of both dialogic interaction (instant
messaging, sms, e-mails, forums, social networks, etc.) and artefact-mediated
interaction (documents, wikis, concept maps); in other words, every time a piece of
information needs to be first coded then decoded in order to pass through the
technological channel.
Apart from its need for codification, the process illustrated in Figure 1, information
transmission, does not differ greatly from the flow of a liquid from one container to
another. This is why it is often defined as an information “flow” (IF).
From information flow to knowledge flow
While Figure 1 adequately represents an IF process, it is inadequate for representing
KF processes. In fact, the mechanisms for the acquisition of new knowledge resemble
less the decanting of a liquid from one container (the sender’s head) to another (the
receiver’s head) than a process of absorption, integration and systematisation of the
received information into the receiver’s own pre-existing cognitive structures, which are
the result of personal experience, earlier knowledge, etc.
Therefore, for a better representation of a KF process the scheme of Figure 1 should be
extended as shown in Figure 2 (Trentin, 2011b).
1 In communication theories the concept of “noise” is understood in a broader sense. Besides the actual
physical noise introduced by technology (e.g. electromagnetic perturbations), it includes noise caused by the following: semantic factors (i.e. different interpretations of the meaning of what is being communicated); entropy and overabundance of information transmitted; difference in interlocutors’ cultural levels; technical jargon of the specific communication context, etc.
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Figure 2 - From Information Flow to Knowledge Flow.
The key point is thus to create the conditions for stimulating the process of
assimilation and accommodation (Piaget, 1977), by proposing both individual and
collaborative learning activities, problem-solving and artefact development, etc.
(Trentin, 2010).
An interesting way of fostering collaborative knowledge building (Scardamalia, &
Bereiter, 1994; Stahl, 2000) is the integration of face-to-face and online interactions
within the virtual community environment, in other words applying what Cress and
Kimmerle call the co-evolution model (Cress, & Kimmerle, 2008), centred on the use of
technologies which favour social interaction.
Such social interaction increasingly tends to develop in hybrid spaces, i.e. where the
increasing portability of mobile technologies and increasing frequency of social media
use tends to annul the clear distinction between onsite and online, producing a kind of
interpenetration of the two in a single a-dimensional space which we often define in fact
as “hybrid”.
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The possible dimensions of KFs
Figure 2 gave a possible representation of the KF process from the point of view of
technology-mediated communication theories. It may now be useful to consider the
intrinsic features of these flows and their contribution to knowledge maturing processes
(Kaschig, Maier, Sandow, Lazoi, & Barnes, 2010). In Figure 3, different types of KF are
identified (Trentin, 2011b):
the Formal -> Informal axis identifies the context in which the flow is developed.
Activities pertaining to a direct educational action, e.g. e-learning, belong to formal
KF, whilst use of NMTs to access and share either explicit Web knowledge or tacit
knowledge stimulated by interactions within online communities belongs to
informal KF;
the Vertical -> Horizontal axis identifies the direction in which the KF spreads.
The flow is vertical when the knowledge is taken from an authoritative and certified
source (a specialised information source, an expert); the flow is horizontal when
knowledge is made to circulate within a community.
Figure 3 – The possible dimensions of KFs.
Four main squares may be identified where the axes cross (Trentin, 2011b):
1. Formal/Vertical KF: the lesson of an expert, the study of materials proposed by the
teacher within a course, etc.;
2. Formal/Horizontal KF: collaborative study during participation in a course, etc.;
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3. Informal/Vertical KF: occasional interaction with an expert, independent
consultation of handbooks and authoritative documental sources, etc.;
4. Informal/Horizontal KF: peer interaction among colleagues outside a programmed
and managed educational course, collaboration in professional problem-solving,
etc.
DEFINITION OF EXPERIMENTAL SETTING
Sixty-six (66) students (38 female, 28 male) enrolled in the NT&KF-2012 course
participated in the experiment. Most of them were aged between 23 and 25 years, 16 of
them between 26 and 34 years; 14 of these 16 were already working in medium-high
profile jobs.
No particular criterion was followed in the composition of the learning groups except
for equal distribution of students with working experience over the various groups. This
was to ensure that there was at least one member within each group who could create a
bridge between what was to be studied theoretically and the operational practice
required in the working world.
The NT&KF-2012 course had a six-monthly duration and included moments of online
activity alternated with 2-hour classroom activities. The latter were mostly dedicated to
(a) students’ requests for clarification from the teacher, (b) the completion of distance
collaborative activity and in our case, (c) the individual compilation of the data sheets.
The experiment was conducted during one of the last modules, precisely “Module 4 –
Online communities of professionals”.
Course technologies
The BYOD (Bring Your Own Device) (Siddiqui, 2014) approach was adopted in the
course, helped by the students’ personal possession of adequate technological devices.
In fact an initial investigation revealed that of the 66 students: